Deep Learning Tutorial 2019

DSAI DEEP LEARNING TUTORIAL

Registration

Syllabus

Installations

Contacts

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Registration deadline: July 7, 2019

Scope
The Data science and artificial intelligence (DSAI) research axis of ICube offers a two-day tutorial targeting researchers from all scientific backgrounds interested in the fast developing area of deep learning from a practical standpoint. The purpose of this event is to help participants build up the basic skillset necessary for understanding, training and running deep neural networks that may benefit their respective research activities. A wide array of topics will be covered with a heavily hands-on approach - from fundamental concepts and programming skills to state-of-the-art deep learning libraries and models - through a series of practicals, given by experienced PhD students and researchers. The tutorial will introduce participants to the libraries using Jupyter notebooks and help researchers desiring to apply DSAI approaches to analyze their data, such as images, videos, text, etc. ICube researchers with interest in deep learning are hereby encouraged to join the tutorial by subscribing via the registration link.
Participation Pre-requisites
Participation is by registration. Limited space is available and the slots are given on a first come first serve basis. In addition, a participant needs the following: A laptop Basic programming skill Deep learning libraries installable via the Packages menu Training dataset downloadable from the Dataset menu If you have hitches in accessing any file or completing the necessary installations before the program days, keep on watching this space, a date will be announced later to resolve all preparatory installation issues.
Date & Venue
Date & Time: September 26 - 27, 2019, 9:00am-5:30pm daily Venue: ICube Laboratory, 300 Bd Sébastien Brant, 67400 Illkirch-Graffenstaden (Room to be announced later.) Google map direction	ICube Laboratory
Program The courses will run for 2 days. Participants will be able to attend both sessions. The detailed syllabus will be accessible via link on the menu bar. However, an abridge form is presented as follows:
Day 1 Time Topic Speaker 09:00-10:00 Introduction to deep learning concepts Nicolas Padoy 10:00-10:30 Coffee Break 10:30-12:30 A primer on Python for deep learning Tong Yu 12:30-14:00 Break/Lunch 14:00-16:00 Introduction to PyTorch Vinkle Srivastav 16:00-16:30 Coffee Break 16:30-17:30 Unistra HPC (to confirm) TBA	Day 2 Time Topic Speaker 09:00-11:00 Introduction to TensorFlow Armine Vardazaryan 11:00-11:30 Coffee Break 11:30-12:30 Using state of art models in TensorFlow (part 1) Chinedu Nwoye 12:30-14:00 Break/Lunch 14:00-15:00 Using state of art models in TensorFlow (part 2) Chinedu Nwoye 15:00-15:30 Coffee Break 15:30-17:30 TBA Thomas Lampert

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Speakers
Nicolas Padoy Professor University of Strasbourg.	Chinedu Nwoye PhD Student University of Strasbourg.	Tong Yu PhD Student University of Strasbourg.	Armine Vardazaryan Research Engineer ICube Laboratory.	Vinkle Kumar Srivasta PhD Student University of Strasbourg.
Thomas Lampert Post-doc researcher University of Strasbourg.	HPC representative --- University of Strasbourg.
General Information
News [ 10/06/2019 ]: Registration for the DSAI deep learning tutorial is open. [ 06/06/2019 ]: Deep learning tutorial website is up.			Contact us Send your questions to this email and we will get back to you. Board Email: dltutorialboard.dsai@icube.unistra.fr